Minimizing the harm to organs at risk, while maximizing the effectiveness of treatment, requires precise determination of actual dose delivered and a comparison to the treatment plan.
This treatment plan, prepared following the prescription of the radiation oncologist, requires precise, accurate, and consistent delivery of an optimal radiation dose to the tumor while simultaneously reducing the side effects on healthy surrounding tissues.
At present, state-of-the art radiation therapy includes using a multi-leaf collimator to modulate the intensity of the radiation beam produced by a particle beam accelerator, such as a LINAC (conventional radiation-emitting, linear accelerator), to better shape the radiation dose distribution in order to minimize irradiation of non-tumorous cells. A multi-leaf collimator (MLC) is a device made up of individual “leaves” of metal, typically high atomic-number materials such as tungsten. The leaves move independently in and out of the beam aperture in order to partially block the beam. MLCs typically include two banks of opposing leaves. In typical examples, each bank has from approximately 50 to 200 leaves, each leaf having a width in the range from about 0.25 cm to about 2 cm (projected at isocenter). A given leaf in a bank and the opposite one in the other bank form a “leaf pair”; they can move one against the other (thus obstructing the beam) or apart (creating an aperture which, in most installations, can be also asymmetric with respect to the central beam axis [leaf overtravel]). Accordingly, today's treatment plans rely on a properly functioning MLC for Intensity Modulated Radiation Therapy (IMRT). Ideally, verification, in real time, that the MLC is properly operating would allow adaptions to subsequent treatment plans or even an adaptation during delivery
The delivered dose may vary from the intended (planned) treatment dose due to a number of factors. These factors include the wrong treatment planning system (TPS) calculation, an error or fault in the physical movement of the LINAC, including its collimating system, or an incorrect beam energy of the LINAC, errors in patient positioning, or changes in the patient's anatomy.
Risks of errors is particularly high in the case of plans with high modulation (i.e. a highly conformal dose distribution is obtained with a complex dynamics of the MLC, in such a way that many small beams contribute to the overall dose).
The effect of errors on patient's health is then amplified in the case of stereotactic treatments, in which the overall treatment dose is delivered in one or a few fractions (i.e. treatment sessions) instead of using the more traditional approach of many fractions (e.g. 20-30) delivered in subsequent days. Stereotactic treatments are appealing since they increase workflow efficiency, reduce problems related to inter-fractional anatomy changes and, in some cases, present a radiobiological advantage. However, delivering a wrong dose may have severe and irreparable consequences.
In traditional pre-treatment quality assurance (QA), a phantom-based detector rests on the couch (replacing the patient) and is irradiated with the treatment plan. This test reveals calculation errors and systematic LINAC errors, and sometimes resulting dose distributions are projected into the patient anatomy with the assumption that it conforms to the CT scan taken at the time of planning. However, this test is not effective against lack of LINAC repeatability, positioning errors, and anatomical changes, as it is done in a special QA fraction and not during patient treatment. Additionally, such pre-treatment QA adds an additional step in the clinical workflow, reducing its efficiency.
Radiation sensors suited to quality assurance categorize as either passive or active sensors. Passive sensors cannot alone produce a signal, thus they need to be coupled to a readout system after irradiation. Examples of passive sensors include radiographic and radiochromic films, gels, sensors based on optically- or thermally stimulated luminescence. Active sensors, permanently connected to an electronic readout system, immediately provide a readout signal during irradiation. Examples of active sensors include semiconductor diodes or ion chambers. Active sensors are preferable since they are easier and faster to use, thus increasing the efficiency of the radiotherapy workflow. Moreover, these detectors allow the instantaneous signal readout (not only integrated signal) and are suited to track dynamical changes.
Well known examples of active sensors for radiotherapy include diodes and ionization chambers. U.S. Pat. No. 6,125,335 describes an example of a diode detector having a beam profiler which is in the form of an array of 46 sensor diodes and an off-axis horizontal sensor diode array. Another example of a typical beam profiler is a multi-sensor radiation detector array, such as the Profiler Model 1170 by Sun Nuclear Corporation of Melbourne, Fla., USA.
Active sensors, typically organized in an array, provide the spatial resolution necessary to verify the complex radiation patterns generated by an MLC. Known ionization chamber arrays include a device described by Bonin et al., “A pixel chamber to monitor the beam performances in hadron therapy” published in Nuclear Instruments and Methods in Physics Research, No. A 519 (2004) at pages 674-686. This device includes a 2-D array of 1024 successive ionization chambers arranged in a regular matrix of 32×32 pixels.
Ionization chambers generally work by providing a high-voltage difference between two electrodes. A gas or liquid fills the space between the electrodes. Typically, this gas is air, nitrogen or an organic gas. Alternatively, an electrically insulating liquid fills this space. The medium gets ionized when exposed to radiation. The ions move towards the electrodes and their charge is collected. An external electrometer measures this charge. The ionization of a molecule of the medium requires a known average energy and, depending on the gas and on the irradiation type, the collected charge is directly proportional to the energy deposited in the gas.
U.S. Pat. No. 4,988,866 describes yet another dosimetry device having a limited number of specifically located sensors for measuring. This device has at least two significant shortcomings. First, due to its configuration and limited number of sensors, it cannot verify the structure of a radiation field of any size. Second, the device can only measure a very narrow energy range due to the single absorber.
Still another dosimetry device, described in DE-101 43 609, improves the spatial resolution of measurement without increasing the number of individual sensors. A set of sensors arranged in a first line and positioned on a rotatable support are located at a different radius from a second line of sensors. The support successively rotates along an angle of 1° or 2°. Successive measurements by lines of sensors taken at angular steps result in a set of many measurement points, thus giving higher spatial resolution. However, this device requires a mechanical drive for the sensor, and the measurement is more time-consuming. In addition, because one takes a set of measurements at successive times, one relies on the stability and constancy of the radiation source. This device cannot measure radiation beam energy.
Although some of the devices of the state of the art measure energy using build-up plates of different thicknesses, the user must enter into the treatment room to perform the measurement several times with the required build-up plate for different energies.
Yang, Y. and Xing, L. describe a method for determining the position of a leaf of a MLC in “Using the volumetric effect of a finite-sized detector for routine quality assurance of multi leaf collimator leaf positioning” Med. Phys. 30 (2003) 433-441. They disclose a finite-size detector, such as an ion chamber, positioned on one leaf as projected in the isocenter plane. Leaf-position displacement increases or decreases the irradiated volume of the detector; therefore, measurement of dose relates to a leaf position error.
Islam et al., in U.S. Pat. No. 8,119,978, issued 2012 Feb. 21, describes an area integrating fluence-monitoring sensor for measuring radiation dose. The sensor consists of at least one gradient ion chamber having a volume gradient across its length.
To detect LINAC errors, which may not be present during first plan delivery, and to increase the efficiency of the clinical workflow, the QA measurement repeats for each treatment fraction while the patient lies on the couch (in-vivo QA). One important benefit is that in-vivo QA enables treatment interruption if something starts to go wrong.
Early attempts for in-vivo QA taught taping a few point detectors (usually diodes) to the patient's skin. This verification, however, was limited to few points and measurement uncertainty was high (conversion from the dose measured at skin level and the one in the target depends on many parameters). In addition, these detectors introduced a perturbation to dose distribution. This method requires positioning of the probes in areas of flat dosimetric gradients, which is usually not given for Intensity Modulated Treatments.
More recent known devices incorporate either entrance (transmission) or exit (portal) detectors.
Other known devices allow the user to evaluate the beam fluence, and thus to project results into the patient's anatomy. Fluence detectors estimate dose perturbation based on detected errors and modify the revealed dose distribution inside the patient accordingly using a dose engine combined with the patient's CT images. Updated images of the patient (e.g. taken with CBCT) in lieu of the planning CT scan can account for positioning errors and any anatomical changes.
Various solutions are known for verifying in vivo the dose distribution in a patient. A first solution uses transmission detectors. The detector positions between the LINAC's collimating system and the patient. The collection of measured data (not perturbed by the patient and the couch) is accomplished by sensors with high-dosimetric performance, such as ion chambers.
Müller in U.S. Pat. No. 8,160,204 issued 2012 Apr. 17, for example, teaches the determination of photon and electron fluence distributions based on measurements. Comparing the expected detector response (calculated from the patient plan on a detector model) to measured data enables a calculation of the difference between actually delivered fluence and the planned fluence.
One particularly well suited detector includes the MatriXX brand detector paired with the COMPASS 3D brand software tool, both available from IBA Dosimetry GmbH (Bahnhofstrasse 5, 90592 Schwarzenbruck, Germany). This is a system for 3D treatment plan and delivery verification and patient dose analysis, giving clinically relevant data analysis. The software component of this detector reconstructs dose from measured fluence, compares the patient plan with measurements, and provides 3D dose deposition information inside the patient's anatomy. Accordingly, this arrangement enables visual or statistical plan evaluation (evaluating dose differences/gamma relative to TPS inside patient CT or on a structure-by-structure statistical/quantitative basis via comparison of the TPS generated DVHs to that of this device's independently calculated DVHs).
Drawbacks of these known detectors include perturbation of the beam under measurement, reduced space between the patient's head and the couch, and loss of the option of mounting additional accessories at the LINAC. Additionally, radiation scattered from the LINAC's head and collimator, which does not contribute to the dose in the patient, complicates the beam measurement, and modeling with available dose engines and predicting the response becomes difficult.
A second solution, a system based on portal imagers, offers a practical solution because most LINAC devices are equipped with a system for portal imaging (typically an amorphous-silicon flat-panel with high spatial resolution) dedicated to control patient positioning. In this example, the QA system consists simply of an additional software. Although there are many commercial solutions available, only few are suited to evaluate the fluence, and calculate the dose in the patient's anatomy. Examples of such commercial systems include EPlgray (available from DOSlsoft, SA, 47 Avenue Carnot, 94230 Cachon, France), and PerFraction (available from Sun Nuclear Corp., 3275 Suntree Blvd, Melbourne, Fla. 32940). All these solutions suffer of similar limitations including: Portal imagers are optimized for patient imaging and positioning—not dosimetry—and thus require complex dosimetric calibration. Fluence has to be back-projected through the patient, increasing uncertainty; and the intensive QA use may cause radiation damage to the detector. Moreover, they usually cover only a part of the maximum field opening and are therefore not suited for all treatments.
A third solution to determine the fluence uses protocol files, such as LINAC log files generated during delivery, to calculate dose values and distributions received by the patient. Commercial products using log files in this way include Mobius 3D with FX extension (Mobius medical). Persons having ordinary skill in this art debate whether log files can provide the same degree of QA reliability as measurements, as they are generated by the system to be monitored itself. Options of suitable transmission detectors include a two-dimensional (2D) array with parallel readout (i.e., each pixel connects to an individual channel of the readout electronics). This enables a true measurement of the 2D fluence distribution. A main limitation of such a 2D detector includes that complexity (e.g. the number of readout channels) increases as spatial resolution is increased. For instance, for a square detector of side length L segmented with a uniform distribution of pixels with pitch h—the number of readout channels is (L/h)2. It is thus difficult to reach a resolution suitable to verify stereotactic treatments, characterized by steep dose gradients. However, two commercial solutions are available: A first commercial solution is the DOLPHIN-branded dosimetry detector, available from IBA Dosimetry GmbH (Bahnhofstrasse 5, 90592 Schwarzenbruck, Germany). It measures the dose using a 2D ion-chamber pixel array (about 1600 pixels with 5 mm pixel pitch projected to isocenter. The Dolphin-brand detector, however, has limitations. For example, alignment of pixels' rows with MLC leaf pairs is not possible since pixel pitch is larger than typical leaves width. Also, due to constraints of pixel ion-chamber design, the Dolphin-brand detector is limited in terms of attenuation, spatial resolution and patient clearance.
A second commercial solution, the ScandiDos Delta4 Discovery brand (available from Scandidos AB, SE-751 83 Uppsala, Sweden) is based on a 2D transmission detector similar to Dolphin brand detector (available from IBA Dosimetry GmbH (Bahnhofstrasse 5, 90592 Schwarzenbruck, Germany). However the ScandiDos device uses a larger number (about 4000) of smaller sensors (silicon diodes), which are aligned with MLC leaf pairs. For online use, it requires a pre-treatment measurement with a phantom-based array to correlate transmission array measurements and dose.
Two-dimensional (2D) arrays with multiplexed readout using large area solid-state technology associates a set of pixels (e.g. a column) to the same readout channel. Complexity increases linearly in relation to the reduction in pixel pitch. However, the cost of solid-state sensors increase more than linearly with area (one pays for the full area, not only the portion covered by pixels). To date there are no commercial applications, although use of MAPS (monolithic active pixel sensors) has been investigated at research level.
An integral ion chamber, covering the full beam area, can be used for QA purposes too (see, e.g., Islam U.S. Pat. No. 8,119,978). A commercial implementation is the detector IQM (from iRT Systems GmbH, Koblenz, Germany). Since a large parallel plate ion chamber would be suitable to track the integrated fluence only, one of the electrodes is inclined in order to introduce sensitivity to rigid displacements of the MLC aperture, as anticipated by the teaching of Barthelmes (U.S. Pat. No. 4,803,368). The IQM is actually composed of two integral chambers mounted back to back, in order to increase the overall detector sensitivity to errors. According to Islam (WO2016191883) the collecting electrode of the integral chamber can be segmented into two interdigitated electrodes with separate readout, in order to obtain with a parallel plate configuration the same error sensitivity which would be given by an inclined electrode, thus simplifying the construction of the device.
One-dimensional (1D) arrays of linear sensors can deliver a complete measurement the number of degrees of freedom of the two-dimensional (2D) fluence distribution generated by the one-dimensional motion of the collimator leaves. Thus, one sensor can monitor the motion of each leaf-pair. An early commercial example is provided by the DAVID system (PTW Freiburg, Germany), based on an array of wire ion chambers (one wire is associated to each leaf pair). Measurements taken with this detector during a given fraction are compared with a baseline measured during or before the first fraction (which is assumed to be in agreement with the plan), in order to perform a constancy check.
With a more complex arrangement, 1D linear detectors can do more than performing a constancy check or measuring the integrated fluence. In particular, it is possible to determine the position of a pair of leaves and not the true dose. One example is a one-dimensional (1D) scintillating fiber optic array developed by Beaulieu et al. (see for example U.S. Pat. No. 8,183,534, which describes a scintillating optical fiber placed below each leaf pair, and a readout at both extremities using two photodiodes. Fiber optic arrays, however, are difficult to calibrate, prone to radiation damage, and are less suited for beam monitoring.
If the 1D array measures the position of a leaf instead of a true dose, it can be relatively insensitive to electron contamination and can work with a minimal buildup. In this way, beam perturbation can be minimized. Such an 1D array detector can also estimate the flux (space integral of fluence), but not the true 2D fluence (e.g. one has to assume a given beam profile e.g. from TPS commissioning.
The above considerations yield the rationale for developing an improved detector for online measurement of radiation dose distribution during treatment, when the patient is in position on the couch.